Research Article

Related GMR Articles

2017 Feb 08
Brazil; Breeding; Crosses, Genetic; Fusarium; Genetic variation; Genotype; Multivariate analysis; Plant Diseases; Tracheophyta

The multivariate analyses are useful tools to estimate the genetic variability between accessions. In the breeding programs, the Ward-Modified Location Model (MLM) multivariate method has been a powerful strategy to quantify variability using quantitative and qualitative variables simultaneously. The present study was proposed in view of the dearth of information about popcorn breeding ... more

R.N.F. Kurosawa; A.T. do Amara Junior; F.H.L. Silva; D. Santos; M. Vivas; S.H. Kamphorst; G.F. Pena
10/04/2007
Clustering; Gene expression; Gene-gene interactions; Supervised learning

We show here an example of the application of a novel method, MUTIC (model utilization-based clustering), used for identifying complex interactions between genes or gene categories based on gene expression data. The method deals with binary categorical data which consist of a set of gene expression profiles divided into two biologically meaningful categories. It does not require data ... more

L.S. Coelho; M.A. Mudado; B. Goertzel; C. Pennachin
03/30/2006
Clustering; Data vizualization; Gene Ontology; Microarray data analysis; Normalization; User-friendly system

SpotWhatR is a user-friendly microarray data analysis tool that runs under a widely and freely available R statistical language (http://www.r-project.org) for Windows and Linux operational systems. The aim of SpotWhatR is to help the researcher to analyze microarray data by providing basic tools for data visualization, ... more

T. Koide; S.M. Salem-Izacc; S.L. Gomes; R.Z.N. Vêncio
09/30/2008
Clustering; Gene expression; Most expressed sequences; Similarity measure

Following sequence alignment, clustering algorithms are among the most utilized techniques in gene expression data analysis. Clustering gene expression patterns allows researchers to determine which gene expression patterns are alike and most likely to participate in the same biological process being investigated. Gene expression data also allow the clustering of whole samples of data, which ... more

S.A.P. Pinto; J.M. Ortega
07/25/2011
Clustering; Genetic correlation; Genetic diversity; Heritability; Oil content

Jatropha curcas, internationally and locally known, respectively, as physic nut and pinhão manso, is a highly promising species for biodiesel production in Brazil and other countries in the tropics. It is rustic, grows in warm regions and is easily cultivated. These characteristics and high-quality oil yields from the seeds have made this plant a priority for biodiesel programs ... more

R.G. Freitas; R.F. Missio; F.S. Matos; M.D.V. Resende; L.A.S. Dias
01/22/2013
Clustering; Genetic similarity; Molecular polymorphism; Variability

Maize landraces derived from tropical germplasm represent an important source of genetic variability, which is currently poorly understood and under-exploited by Brazilian crop breeding programs. The aims of our study were to a) estimate the genetic diversity across 48 varieties of maize landraces cultivated at different locations in the States of Rio Grande do Sul (RS) and Paraná (PR) by ... more

D. Molin; C.J. Coelho; D.S. Máximo; F.S. Ferreira; J.R. Gardingo; R.R. Matiello
09/12/2014
Clustering; Genetic diversity; Heterotic pools; Microsatellites

The objectives of this study were to identify the population structure and to assess the genetic diversity of maize inbreds. We genotyped 81 microsatellite loci of 90 maize inbreds that were derived from tropical hybrids and populations. The population structure analysis was based on a Bayesian approach. Each subpopulation was characterized for the effective number of alleles, gene ... more

E.C.M. Lanes; J.M.S. Viana; G.P. Paes; M.F.B. Paula; C. Maia; E.T. Caixeta; G.V. Miranda
09/08/2015
Conilon coffee; Fertilization; Mineral nutrition

The expansion of agriculture to new areas in order to increase the competitiveness of coffee producing countries has resulted in cultivation expanding into regions with lower natural fertility. This scenario has created the need to differentiate genotypes of Conilon coffee based on their tolerance to low levels of nutrients in the soil, especially phosphorus, which imposes high ... more

L.D. Martins; W.N. Rodrigues; L.S. Machado; S.V.B. Brinate; T.V. Colodetti; J.F.T. Amaral; M.A. Tomaz
10/06/2016
Cluster; Conilon coffee; Mean leaf nutrient content; Mineral nutrition; Sampling time

Diagnosing foliar nutritional status is essential for fertilizer recommendations and for the identification of nutrient imbalances. This study aimed to verify genetic diversity and establish mean standards (leaf nutrient contents; LNCs) and relationships among leaf nutrients (LNC relationships; LNCRs) in seven conilon coffee genotypes during both pre-flowering and bean-filling stages. ... more

W.R. Gomes; W.P. Rodrigues; H.D. Vieira; M.G. Oliveira; J.R.M. Dias; F.L. Partelli; W.R. Gomes; W.P. Rodrigues; H.D. Vieira; M.G. Oliveira; J.R.M. Dias; F.L. Partelli
12/31/2019
Conilon coffee; Leaves; Linear measurements; Non-destructive method

Knowledge of the leaf characteristics of the coffee tree, such as leaf dimensions, is of great importance for management of this crop, since it directly impacts on plant development. We evaluated the genetic diversity of 43 Coffea canephora genotypes and developed and compared mathematical models for estimating the leaf area of distinct genotypes using ... more

D. Dubberstein; L.D. Martins; A. Ferreira; J.H. Guilhen; J.C. Ramalho; F.L. Partelli

Pages